import numpy as np
import matplotlib.pyplot as plt
import h5py
import scipy
from PIL import Image
from scipy import ndimage
from lr_utils import load_dataset
from model import model

train_set_x_orig, train_set_y, test_set_x_orig, test_set_y, classes = load_dataset()
train_set_x = train_set_x_orig.reshape(train_set_x_orig.shape[0], -1).T/255
test_set_x = test_set_x_orig.reshape(test_set_x_orig.shape[0], -1).T/255
d = model(train_set_x, train_set_y, test_set_x, test_set_y, num_iterations = 2000, learning_rate = 0.005, print_cost = True)